A Comprehensive Database for Benchmarking Imaging Systems

• Published in: IEEE transactions on pattern analysis and machine intelligence Vol. 42; no. 3; pp. 509 - 520
• Main Authors: Panetta, Karen, Wan, Qianwen, Agaian, Sos, Rajeev, Srijith, Kamath, Shreyas, Rajendran, Rahul, Rao, Shishir Paramathma, Kaszowska, Aleksandra, Taylor, Holly A., Samani, Arash, Yuan, Xin
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.03.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adolescent; Adult; Aged; Algorithms; Automated Facial Recognition - methods; Benchmarking; Cameras; Child; Child, Preschool; Colleges & universities; computerized face sketches; cross-modality; Databases, Factual; Face; Face - anatomy & histology; Face - diagnostic imaging; Face recognition; Female; Humans; Image acquisition; Image Processing, Computer-Assisted - methods; Image recognition; Imaging, Three-Dimensional; Infrared imagery; Infrared photography; Machine learning; Male; Middle Aged; near infrared; The tufts face database; thermal; Three-dimensional displays; Young Adult

Cross-modality face recognition is an emerging topic due to the wide-spread usage of different sensors in day-to-day life applications. The development of face recognition systems relies greatly on existing databases for evaluation and obtaining training examples for data-hungry machine learning alg...